The demand for AI continues to accelerate. Workloads are getting larger, models are becoming more complex, and there is mounting pressure to deploy AI compute infrastructure faster than ever. AI factories —data center-scale systems that continuously convert data and energy into intelligence—are being deployed to meet this insatiable demand.

This AI factory approach to the data center has fundamentally changed system design and operation. Peak accelerator FLOPS are no longer enough. Today’s AI workloads, including trillion+ parameter models, mixture-of-experts (MoE) architectures, long-context reasoning, and disaggregated serving, require many accelerators working together as a single unit of compute. Achieving this requires high-bandwidth, low-latency GPU-to-GPU communication, fast in-network compute for collectives, and software-aware scheduling.

Given the sheer number of components, resiliency needs to be built into the entire data center.…